Closed-loop digital twin technology provides the most significant and immediate impact from Industrial IoT solutions.
The closed-loop digital twin mirrors the entire, fully connected product lifecycle, and it enables changes based on live data.
This live data can then be used to track machine performance and compare the machine’s expected use versus its actual use.
When fully realized, the same data can be fed back into designs to make real-time adjustments and simulation updates.
Once it all comes together, the closed-loop digital twin leads to industrial innovation and infrastructure.
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Technology Innovation in Manufacturing Process
To gain a competitive advantage, manufacturers must continue to push the boundaries of technology and advance their processes.
The world of manufacturing has become more global and more competitive than ever, and digitalization can help today’s machine and equipment builders thrive in the future.
The power of the Industrial Internet of Things (IIoT) is apparent, and forward-thinking companies are pioneering new ways to leverage it.
Combining digital twin technology with product lifecycle management (PLM) systems creates the closed-loop digital twin, which can help companies optimize their product and their manufacturing process.
Industrial IoT Solutions and the Benefits of IoT in Manufacturing
Using digital twins across design, the production cycle, and for products in the field extends industrial IoT solutions into realms unrealized by most machine and equipment manufacturers.
Creating digital twins for the product, production, and performance all connect to create a closed feedback loop, ensuring performance data from products in the field and from production environments feed into the product and production.
The benefits of these industrial IoT solutions include:
- Downtime reduction
- Reduced maintenance costs
- Improved equipment performance and reliability
- Extended asset lifespan
Predictive Maintenance Machine Learning
Smarter maintenance can be extended into every area of production when manufacturers take advantage of closed-loop digital twin technology.
By incorporating real-world usage data and virtual simulations, manufacturers can optimize maintenance based on the age of the machine, runtime, and possible exposure to harsh conditions.
Additionally, machine users can schedule maintenance to minimize disruptions to any operations.
Taking it a step further, machine learning can help manufacturers peer into the future to determine maintenance needs to extend asset lifespan and minimize parts inventory.
With the closed-loop digital twin informing maintenance schedules, manufacturers can reduce the chance of an unexpected event or emergency.